Generation of voxelized breast phantoms from surgical mastectomy specimens. Issue 4 (29th March 2013)

• Record Type: Journal Article
• Authors: Michael O'Connor, J.; Das, Mini; Dider, Clay S.; Mahd, Mufeed; Glick, Stephen J.
• Is Part Of: Medical physics. Volume 40:Issue 4(2013)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2013-03-29
• Subjects: Computed tomography; computerised tomography -- phantoms; breast CT -- tomosynthesis -- mammography -- phantom -- simulation; Computerised tomographs; Medical imaging -- Computed tomography -- Medical image reconstruction -- Image sensors -- Tissues -- Medical X‐ray imaging -- Image reconstruction -- Medical image noise -- X‐ray detectors -- Diffusion; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4795758
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: : In the research and development of dedicated tomographic breast imaging systems, digital breast object models, also known as digital phantoms, are useful tools. While various digital breast phantoms do exist, the purpose of this study was to develop a realistic high‐resolution model suitable for simulating three‐dimensional (3D) breast imaging modalities. The primary goal was to design a model capable of producing simulations with realistic breast tissue structure. Methods: : The methodology for generating an ensemble of digital breast phantoms was based on imaging surgical mastectomy specimens using a benchtop, cone‐beam computed tomography system. This approach allowed low‐noise, high‐resolution projection views of the mastectomy specimens at each angular position. Reconstructions of these projection sets were processed using correction techniques and diffusion filtering prior to segmentation into breast tissue types in order to generate phantoms. Results: : Eight compressed digital phantoms and 20 uncompressed phantoms from which an additional 96 pseudocompressed digital phantoms with voxel dimensions of 0.2 mm 3 were generated. Two distinct tissue classification models were used in forming breast phantoms. The binary model classified each tissue voxel as either adipose or fibroglandular. A multivalue scaled model classified each tissue voxel as percentage of adipose tissue (range 1%–99%). Power spectral analysis was performed to compare simulated reconstructions using the breast phantoms to the original breast specimen reconstruction, and fits were observed to be similar. Conclusions: : The digital breast phantoms developed herein provide a high‐resolution anthropomorphic model of the 3D uncompressed and compressed breast that are suitable for use in evaluating and optimizing tomographic breast imaging modalities. The authors believe that other research groups might find the phantoms useful, and therefore they offer to make them available for wider use.